EP1700245B1 - Procede, installation et programme informatique permettant d'estimer la taille initiale d'une population d'acides nucleiques, en particulier par pcr - Google Patents

Procede, installation et programme informatique permettant d'estimer la taille initiale d'une population d'acides nucleiques, en particulier par pcr Download PDF

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EP1700245B1
EP1700245B1 EP05815440A EP05815440A EP1700245B1 EP 1700245 B1 EP1700245 B1 EP 1700245B1 EP 05815440 A EP05815440 A EP 05815440A EP 05815440 A EP05815440 A EP 05815440A EP 1700245 B1 EP1700245 B1 EP 1700245B1
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Prior art keywords
interest
sample
index
population
yield
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German (de)
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EP1700245A1 (fr
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Karine Piot
Pierre Martineau
Claire Lamoure
Franck Molina
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Centre National de la Recherche Scientifique CNRS
Bio Rad Innovations SAS
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Centre National de la Recherche Scientifique CNRS
Bio Rad Pasteur SA
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Priority claimed from FR0412471A external-priority patent/FR2878350B1/fr
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/10—Signal processing, e.g. from mass spectrometry [MS] or from PCR

Definitions

  • the present invention relates to estimating the initial size of a population of interest in a sample subjected to a succession of amplification reactions.
  • the present invention finds a particularly advantageous, but non-limiting, application in determining an initial quantity of nucleic acids in a sample subjected to a polymerase chain reaction (PCR) in real time.
  • PCR quantification A technique of this type, known as "PCR quantification", is used in particular for evaluating the number of copies of pathogenic agents (e.g. of the human immunodeficiency virus (HIV)) in a sample of body fluids taken from a patient, typically in the context of a medical checkup.
  • pathogenic agents e.g. of the human immunodeficiency virus (HIV)
  • FIG. 1 For a brief description of the diagrammatic appearance of a real time PCR amplification curve with PCR cycle index numbers plotted along the abscissa and, in the example shown, with quantities of fluorescence emitted (in arbitrary units) as measured for each PCR cycle plotted up the ordinate.
  • F n By plotting the measured fluorescence F n as a function of PCR cycle number n, variation is obtained of the type shown in Figure 1, and comprises at least:
  • the greater the initial quantity of nucleic acids in a sample the sooner a detectable quantity of PCR product is obtained, i.e. the sooner a detectable quantity of emitted fluorescence is obtained.
  • the initial population in the standard St1 is greater than that in the standard St2 which is greater than that in the standard St3, etc., since the cycle Ct1 for the standard St1 occurs before the corresponding cycle Ct2 for the standard St2, which occurs before the cycle Ct3 for the standard St3, etc.
  • such a CT cycle corresponding to the cycle at which the fluorescence measurements reach a fluorescence threshold THR (as shown in Figure 2), sets at an arbitrary level (typically below the background noise), and acts as a parameter representative of the initial size N 0 of a population of nucleic acids subjected to the PCR cycles.
  • THR fluorescence threshold
  • cycle numbers Ct1, Ct2, Ct3, Ct4 for a plurality of standards having known initial populations, and their initial populations N 0 1 , N 0 2 , N 0 3 , N 0 4 .
  • a regression slope REG is obtained.
  • the cycle Ctint detected for the sample of interest is plotted (dashed-line arrow F1).
  • the initial population size N 0 int is then determined for the sample of interest.
  • the method depends on the judgment of the user, since the fluorescence threshold value, as selected by the user, has a direct influence on the values of the Ct cycles in the amplification curves, and consequently on the estimated values for the initial population size in the sample of interest.
  • the threshold value also has an impact on the accuracy of the result, since accuracy is generally better if the threshold is selected to lie in the exponential growth stage EXP of the amplification curve. Nevertheless, in practice, it is difficult for the user to know whether the fluorescence threshold level THR that has been set does indeed correspond to the exponential stage of the curves, and does so for all of the samples (the standard samples and the sample of interest).
  • the method assumes without any verification that the population has the same amplification yield in the sample of interest and in all of the standard samples. Thus, if the sample of interest contains PCR inhibitors, as is typically the case, then its result will be falsely lowered.
  • the prior art technique depends on the fluorescence threshold THR as defined by the user.
  • the value selected has an influence on the values of the Ct cycles and consequently on determining the initial quantity in the sample of interest. That is one of the reasons why a large amount of work has recently been undertaken to automate Ct cycle detection and make it reliable.
  • the present invention seeks to improve the situation by proposing an approach that is completely different.
  • the invention provides a method, the method being implemented by computer means for quantifying in absolute and/or relative manner an initial population of nucleic acids in a sample of interest.
  • the sample is subjected to a succession of applications of a reaction for amplifying the population of interest.
  • this amplification may be undertaken by implementing successive PCR cycles, however any other amplification technique could also be used.
  • aLl it should be understood that the amplification needs merely to be defined by a reaction yield, as described below.
  • experimental measurements are taken that are representative of a current population size, at least in the sample of interest. It will be understood that one or more measurements can be taken after or during each amplification reaction without loss of generality.
  • the method in the meaning of the invention comprises the following steps:
  • Figure 4A plots a succession of experimental measurements F n representative of the current size of a population of interest which is being subjected progressively to a succession of amplification reactions, each reaction being indexed by an index number n .
  • this succession of reactions corresponds to a succession of PCR cycles.
  • the experimental measurements F n correspond to measured quantities of fluorescence on each PCR cycle.
  • the measurement method may make use of techniques other than fluorescence, even if fluorescence is the method that is often used for quantifying by PCR.
  • other amplification techniques could be implemented in the context of the present invention, providing it is possible to track variation in the yield of the reaction corresponding to the amplification. Since the example described below relates preferentially to PCR cycles, reference is made to the "effectiveness of the PCR" written E n for each PCR cycle of index n , in order to refer to the yield of the amplification reaction.
  • Figure 4A mainly comprises two regions in which:
  • This decrease in yield may have a variety of explanations, in particular a degradation and/or a lack of PCR reagents (DNA polymerase, dNTPs, primers, etc.) and/or inhibition by the products that are made themselves.
  • PCR reagents DNA polymerase, dNTPs, primers, etc.
  • the objective is to find the initial size of the population that has been subjected to amplification.
  • the measurement F 0 representative of this initial population size which coincides in practice with the measurement background noise BN, cannot be used on its own for determining directly the initial population size.
  • attempts have been made to quantify this initial population size by making use of the exponential stage, i.e. a stage that occurs typically on exiting background noise.
  • a threshold cycle Ct is then determined (corresponding to point PA for "prior art") in Figure 4A.
  • measurements are often affected by noise and it is difficult to determine accurately a threshold cycle Ct representative of exiting background noise.
  • the present invention instead makes use of nearly all of the points of the amplification curve in order to determine accurately a region CHO where the yield changes over between a constant stage and a non-constant, stage, typically in present circumstances between the exponential stage EXP and the linear stage LIN. It will be understood that measurements are logically less affected by noise in this region CHO than in the background noise exit region since the region CHO occurs during later cycles. Furthermore, particularly because of the mathematical properties associated with yield, it is shown below that, most advantageously, the number of standards that need to be used for quantifying the initial size of the population of interest is smaller than the number of standards used in prior art quantification.
  • N n + 1 1 + E n ⁇ 1 + E n - 1 ⁇ 1 + E n - 2 ... 1 + E 0 ⁇ N 0
  • N 0 is the initial size of the population of interest.
  • a first implementation consists in determining the changeover index C EEP experimentally and in correlating it with the initial size by regression by using a plurality of standard samples that are subjected to the same amplification treatment as the sample of interest.
  • steps b) and c) of the above-defined method are merely interchanged since initially the changeover index C EEP (step c)) is determined experimentally, and subsequently the relationship between the index C EEP and the initial size N 0 (step b)) is determined in order to end up with the initial size N 0 (step d)).
  • a prior step of processing the experimental measurements F n is preferably applied, this step consisting in subtracting the background noise BN and subsequently in introducing compensation to take account of a non-zero measurement ⁇ representative of the initial population size.
  • the variation in the background noise BN as a function of the index n can be represented by a linear function since tests have shown that a linear model is satisfactory for fluorescence measurements in PCR. Nevertheless, in certain circumstances it may be preferable to use an exponentially-varying model.
  • a model is applied that complies best with variation in the background noise BN as given typically by the initial measurement points. Thereafter, the selected model for variation in background noise BN is subtracted from all of the experimental measurement values F n .
  • these steps of correcting for background noise are very advantageous in determining the changeover index C EEP , they may also be applied to any determination and quantification of the initial population size N 0 whenever background noise is likely to falsify measurement of said population size N 0 . In this respect, these steps may constitute the subject matter of separate protection, where appropriate.
  • the non-constant stage of yield is decreasing and corresponds to said second region presenting little noise (as shown in Figure 4B).
  • Figure 4B Specifically for the purpose of eliminating measurement points that run the risk of falsifying results when selecting a model to apply to the variation in yield:
  • the changeover region CHO is identified by working in the direction of decreasing index numbers n, starting from the less noisy second region, and by detecting a coarse index CG for which the yield passes a predetermined value.
  • the yield associated with each index number is evaluated. For the first measurement point of yield that is significantly greater than the above-mention ed predetermined value, it is considered that the above-mentioned coarse index CG has been detected and corresponds to the index of the measurement point.
  • each measurement point it is possible for each measurement point to model the variation in its yield as though said set point itself corresponds to the changeover index C EEP .
  • the constant yield stage E 0 is estimated, and if the estimated value exceeds the above-mentioned predetermined value, then the point is considered as corresponding to the coarse index CG.
  • a maximum yield has a value of 1 so it is possible to select the above-mentioned predetermined value as being equal to 1. Nevertheless, this can be varied, and, for example, provision can be made to set the predetermined value as corresponding to the mean yield E 0 as evaluated over the initial reaction cycles.
  • the estimate of the value of the amplification index C EEP in the changeover region is refined, which value may advantageously be a fraction, by working in the direction of increasing amplification index numbers, starting from the coarse index CG, and by detecting an amplification index for which the yield is approximately equal to the above-mentioned predetermined value.
  • a search is made downwards starting from the coarse index CG and going in the direction of increasing index number n , in steps of a size smaller than one whole index, and the abscissa value is determined, e.g. by interpolation, at which the predetermined value is crossed.
  • the search is continued in the direction of increasing number n, and the index (C EEP - 1) preceding the changeover is determined as soon as the constant value E 0 is equal to or very close to 1. That is why it is appropriate to select a search step size corresponding to a fraction of the index, for example 10% of one cycle n .
  • this parameterized variation is representative of the current population size N n in the sample of interest.
  • this variation makes use of a parameter representative of the initial population size No in the sample of interest.
  • step a it is necessary to determine a model for the above-mentioned function function (C EEP , n+1).
  • a model is selected for the non-constant stage of the yield corresponding to a decreasing exponential having a decrease parameter ⁇ which is described in greater detail below.
  • This decrease parameter ⁇ is then determined in step c), at least with the changeover index C EEP , by comparison with the experimental measurements.
  • the measured value of the initial population size F 0 is determined by comparing said parameterized variation F n with the experimental measurements.
  • FIG. 6A shows the amplification curve for a sample of interest containing nucleic acids, in this case a fragment of DNA having an initial quantity of 100,000 copies, marked by the SYBRGREEN intercalant during the PCR reaction which is performed on the I-Cycler IQ® apparatus from the supplier BI-RAD®.
  • the amplification reaction is a PCR reaction in real time.
  • the experimental measurement represents quantities of emitted fluorescence.
  • the fluorescence of cycle n after adjustment for background noise, as described above, is written F n below.
  • the theoretical initial fluorescence before the first cycle is written F 0 .
  • the effectiveness of the PCR in cycle n is written E n .
  • the total number of cycles performed during the PCR reaction is written N.
  • the fluorescence measured on each cycle n of the PCR reaction cycle is defined by: F n + 1 ⁇ F n ⁇ 1 ⁇ + E n for all n ⁇ 1 , 2 , ... , N - 1 with 0 ⁇ E n ⁇ 1.
  • Figure 6B shows the effectiveness of the PCR reaction as approximated by formula (2) and on the basis of the adjusted variation in fluorescence of Figure 6A, as a function of cycle number n .
  • the measured effectivenesses in cycles 1 to 16 are very noisy, which makes it difficult to verify the first assumption graphically.
  • the cycle (C EEP -1) thus represents the last cycle (which may be a fraction) for which effectiveness continues to be constant.
  • some other selection may be preferred, e.g. from the models F1 to F3 given below, particularly depending on the type of nucleic acid that is to be quantified.
  • step c) Preferably, several sets of parameters are estimated in step c) for several candidate changeover cycles C EEP , and the minimum candidate cycle is selected for which the associated parameters maximize the statistical correlations that can be undertaken in step c), for each changeover cycle C EEP .
  • E ⁇ n F ⁇ n + 1
  • F ⁇ n - 1 F n + 1 + ⁇ F n + ⁇ - 1 for all n ⁇ 1 , 2 , ... , N - 1
  • the effectiveness values E' n are approximated experimentally from the measurements so as to be able to set a minimum acceptable effectiveness threshold during the stage of decreasing effectiveness.
  • a threshold cycle is thus determined beyond which the adjusted fluorescence measurements are not used for the purposes of the model (points NEG in Figure 4B).
  • the threshold cycle corresponds to the first cycle in the stage of decreasing effectiveness at which effectiveness drops below some minimum acceptable effectiveness threshold (e.g. 0.1E 0 ).
  • the value of the effectiveness threshold preferably lies in the range 0 to 0.5, and PCR having an effectiveness value below said threshold is potentially biased by uncontrolled inhibition phenomena.
  • the threshold value for effectiveness was set at 0.02 (i.e. 2% of E 0 ).
  • Figure 8 also shows good correlation with experimental measurements for predictive effectiveness as obtained from Figure 7 using the model based on measured and adjusted fluorescence.
  • a start step 70 the measured values for quantities of fluorescence have been obtained and adjusted relative to background noise as a function of cycle number n, as shown in Figure 6A.
  • step 72 the minimum cycle C s is determined for which the following two conditions are satisfied:
  • test 74 on the value ⁇ ' 0 estimated for the value E' 0 and the decrementation in step 75 of the value for the changeover cycle C EEP seeks to find the looked-for value of C EEP using a step size P (which may be equal to 1), and in repeating step 73 so long as the value of ⁇ ' 0 is less than 1.
  • step 76 the value of the index C EEP is incremented by a step of size h (which may be a fraction smaller than unity) in step 76 and in step 77 fluorescence F n is modeled in the same manner as in step 73. So long as the estimated effectiveness ⁇ ' 0 is greater than or equal to 1 in step 78, steps 76 to 78 are repeated. When the estimated effectiveness takes a value of less than 1, the estimated parameters (F ⁇ ' 0 , ⁇ ' 0, ⁇ ' 0 , ⁇ EEP ) are conserved in an end step 79.
  • a value F ⁇ ' 0 has finally been obtained that alone is representative of the initial population size No in the sample of interest. It is then possible to use at least one standard sample having a known population size N 0 st so as to determine in step 80 the initial population size No in the sample of interest.
  • a measured value of an initial population size F 0st in a standard sample of known initial population N 0st is obtained.
  • the value of the initial population size N 0 in the sample of interest is obtained by deriving a proportionality relationship between the measurement for the standard sample and its known initial population size, and applying that relationship to the measurement F' 0 to obtain the actual initial population size N 0 .
  • this dependency relationship may also typically be a regression of the type shown in Figure 5, but having the initial fluorescence values F ⁇ ' 0st and F ⁇ ' 0 of the standards and of the sample of interest plotted up the ordinate (or the values of their respective logarithms) instead of plotting values for the changeover index C EEP .
  • the quantity of fluorescence F ⁇ ' 0st before the first cycle is estimated for the standard(s) using the same method as is used for determining F ⁇ ' 0 for the sample of interest, as described above.
  • a third implementation corresponding to a variant of the above-described second implementation consists overall in adjusting the model for the effectiveness E n relative to the experimental measurements, and in subsequently injecting said adjusted effectiveness model into the model for the current population size N n , or into the model for the measurement F n .
  • This third implementation can be summarized as follows.
  • step b) The parameterized variation constructed in step b) is representative of yield, and in step c), experimental variation of the yield is determined on the basis of experimental measurements in order to compare the parameterized variations with the experimental variation. Thereafter, in order to obtain a parameter representative of the initial population size No the following steps are performed in step d):
  • the present invention can also apply to relative quantification, in particular by PCR.
  • a reference population is also amplified either simultaneously in the same medium, or separately. Measurements are taken as follows:
  • step d) consists merely in determining a ratio between the respective initial sizes of the population of interest and of the reference population.
  • Relative quantification can be used for analyzing the expression of a gene of interest during the development of an organism.
  • a reference gene is also analyzed that is known for having a level of expression that remains stable during development.
  • a final step then consists in comparing the ratios N 0 ⁇ target N 0 ⁇ ref between the various samples that have been taken.
  • the prior art strategy is based on detecting the threshold cycle Ct and it normally takes place as follows. For each sample taken at different instants t0, t1, t2, ..., tn, the ratio N 0 ⁇ target N 0 ⁇ ref is determined, making use of at least one standard (i.e. a standard for which N 0target and N 0ref are known), which amounts to performing two successive absolute quantifications followed by calculating a ratio.
  • FIG. 10 shows an installation for implementing the method of the invention. It comprises a support SUPP in this case comprising a well containing the sample of interest ECH and a well containing a standard sample referenced St, for example.
  • the support SUPP is enclosed in an enclosure ENC, e.g. fitted with heater means (not shown) for applying a PCR reaction to the standard and to the sample of interest.
  • an apparatus for detecting fluorescence comprises, for example, an objective lens 11 for collecting the light coming from the fluorescence, and photon counting means 10, e.g.
  • the fluorescence emitted by each well is advantageously focused by the lens 11 and then is preferably detected by a CCD camera 10 connected to an acquisition card 21, e.g. of the Personal Computer Memory Card International Association (PCMCIA) type provided in a central unit 20 of a computer.
  • PCMCIA Personal Computer Memory Card International Association
  • the computer is then connected to the above-mentioned measuring means 10 to receive therefrom signals that are representative of the measured quantities of fluorescence detected on each PCR cycle, and to process these signals in order to determine an initial size for the population of interest prior to the first cycle, by implementing the method of the invention.
  • the processor unit comprises the following:
  • the computer may also have input members such as a keyboard 41 and/or a mouse 42 connected to the central unit 20.
  • a computer program product can be used for controlling the computer means.
  • the program may be stored in a memory of the processor unit 20 or on a removable memory medium (CD-ROM etc.) and suitable for co-operating with the reader of the processor unit.
  • the computer program in the meaning of the invention then contains instructions for implementing all or some of the steps of the method of the invention.
  • the algorithm of the program may be represented by a flow chart equivalent to the diagram of Figure 9.

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Claims (22)

  1. Procédé mis en oeuvre par des moyens informatiques pour quantifier, de manière absolue et/ou relative, une population initiale d'acides nucléiques dans un échantillon d'intérêt soumis à une succession d'applications d'une réaction d'amplification de la population, durant lesquelles des mesures expérimentales représentatives d'une taille en cours de la population d'au moins l'échantillon d'intérêt sont prises,
    le procédé comprenant les étapes suivantes :
    a) fournir un modèle du rendement de la réaction d'amplification en fonction de la succession d'amplifications, ledit modèle comprenant :
    - une phase substantiellement constante pour une première partie des applications de la réaction d'amplification ; et
    - une phase non constante pour une deuxième partie des applications de la réaction d'amplification ;
    les première et deuxième parties étant réunies par une région de changement dans laquelle le rendement varie entre les phases constante et non constante, ladite région possédant un indice d'amplification correspondant substantiellement au changement ;
    b) utiliser le modèle de rendement pour exprimer une relation impliquant au moins l'indice de changement et un paramètre représentatif de la taille de la population initiale dans l'échantillon d'intérêt ;
    c) déterminer au moins l'indice de changement par comparaison avec les mesures expérimentales ; et, dans une étape d) ultérieure ou immédiatement consécutive, en déduire la taille de la population initiale dans l'échantillon d'intérêt.
  2. Procédé selon la revendication 1, comprenant :
    - à l'étape b), l'utilisation du modèle de rendement pour exprimer une variation qui est paramétrée en fonction de ladite succession d'amplifications, impliquant au moins un paramètre représentant l'indice de changement ; et
    - à l'étape c), la détermination au moins dudit paramètre représentant l'indice de changement par comparaison avec lesdites mesures expérimentales.
  3. Procédé selon la revendication 2, dans lequel ladite variation paramétrée est représentative de la taille en cours de la population dans l'échantillon d'intérêt,
    dans lequel ladite variation implique en outre un paramètre représentatif de la taille de la population initiale dans l'échantillon d'intérêt ; et
    dans lequel, aux étapes c) et d), les paramètres représentatifs dudit indice d'amplification et de la taille de la population initiale dans l'échantillon d'intérêt sont déterminés sensiblement ensemble.
  4. Procédé selon la revendication 2, dans lequel ladite variation paramétrée est représentative du rendement, et dans lequel, à l'étape c), une variation expérimentale du rendement est déterminée à partir desdites mesures expérimentales, afin de comparer la variation paramétrée à la variation expérimentale.
  5. Procédé selon la revendication 4, comprenant, à l'étape d) :
    d1) la détermination d'une deuxième variation paramétrée qui est représentative de la taille en cours de la population dans l'échantillon d'intérêt, et qui implique au moins le paramètre représentant ledit indice d'amplification, et un paramètre représentatif de la taille de la population initiale dans l'échantillon d'intérêt ;
    d2) l'application d'une valeur paramétrée pour l'indice tel que déterminé à l'étape c) à la deuxième variation ; et
    d3) l'ajustement au moins du paramètre représentatif de la taille de la population initiale par comparaison directe de la deuxième variation avec les mesures expérimentales.
  6. Procédé selon la revendication 5, comprenant :
    - à l'étape d2), l'application d'une valeur approximative pour l'indice, alors que
    - à l'étape d3), on affine la valeur de l'indice tout en ajustant également le paramètre représentatif de la taille de la population initiale.
  7. Procédé selon la revendication 3 ou 6, dans lequel ladite variation paramétrée ou ladite deuxième variation paramétrée, selon le cas :
    - est représentative desdites mesures expérimentales ; et
    - inclut un paramètre correspondant à une valeur mesurée représentative de la taille de la population initiale,
    et dans lequel la valeur de mesure de la taille de la population initiale est déterminée en comparant lesdites variations paramétrées aux mesures expérimentales.
  8. Procédé selon l'une quelconque des revendications 1 à 7, comprenant l'application d'une étape préalable de traitement des mesures expérimentales, laquelle étape comprend la soustraction d'un bruit de fond des mesures et l'introduction d'une compensation pour tenir compte d'une mesure non nulle représentative de la taille de la population initiale.
  9. Procédé selon la revendication 7 ou 8, comprenant l'obtention d'une valeur de mesure pour une taille de population initiale dans un échantillon étalon possédant une taille de population initiale connue et la dérivation d'une relation de proportionnalité entre celles-ci ; et la détermination de la valeur de la taille de la population initiale dans l'échantillon d'intérêt par application de la même relation de proportionnalité entre la taille de la population initiale et sa mesure à l'échantillon d'intérêt.
  10. Procédé selon la revendication 7 ou 8, comprenant l'obtention de valeurs de mesure respectives pour les tailles de population initiale dans des échantillons étalons possédant des tailles de population initiale connues, et :
    - l'établissement d'une relation de dépendance entre les tailles de population initiale des échantillons étalons et les valeurs de mesure correspondantes pour leurs tailles de population initiale respectives ; et
    - après détermination de la valeur de mesure pour la taille de la population initiale de l'échantillon d'intérêt, la détermination de la taille initiale de la population d'intérêt par interpolation sur ladite relation de dépendance.
  11. Procédé selon la revendication 9 ou 10, comprenant la fourniture d'un ou plusieurs échantillons étalons possédant des tailles de population initiale connues respectives, l'application de ladite succession d'amplifications auxdits échantillons étalons dans des conditions substantiellement identiques à celles pour l'échantillon d'intérêt, et la détermination de leurs valeurs de mesure initiales effectives par comparaison des variations paramétrées avec les valeurs expérimentales.
  12. Procédé selon la revendication 3, comprenant la fourniture d'une pluralité d'échantillons étalons possédant des tailles de population initiale connues respectives, l'application à ceux-ci de ladite succession d'amplifications dans des conditions substantiellement identiques à celles pour l'échantillon d'intérêt, et la détermination de leurs indices respectifs par l'application des étapes a), b) et c) et, à l'étape d) :
    - l'établissement d'une relation, de dépendance entre les tailles de population initiale des échantillons étalons et leurs indices ; et
    - après détermination de l'indice pour l'échantillon d'intérêt, la détermination de la taille initiale de la population d'intérêt par interpolation sur ladite relation de dépendance.
  13. Procédé selon l'une quelconque des revendications 1 à 8, dans lequel, pour une quantification relative, on fournit non seulement la population d'intérêt, mais également une population de référence qui est soumise à une succession d'applications de la réaction d'amplification, le procédé consistant à prendre, respectivement :
    - des mesures expérimentales représentatives de la taille de la population d'intérêt ; et
    - des mesures expérimentales représentatives de la taille de la population de référence ;
    le procédé se poursuivant par l'application des étapes a), b) et c) à la population de référence, l'étape d) consistant à déterminer un rapport entre les tailles initiales respectives de la population d'intérêt et de la population de référence.
  14. Procédé selon l'une quelconque des revendications 1 à 13, comprenant :
    - l'expression des mesures expérimentales sous la forme d'une variation expérimentale de rendement en fonction de ladite succession d'amplifications ; et
    - l'obtention d'une variation expérimentale de rendement en fonction de ladite succession d'amplifications comprenant :
    - une première région qui est substantiellement soumise à un bruit pour des nombres indices d'amplification faibles ; et
    - suivie d'une deuxième région avec moins de bruit pour des nombres indices d'amplification supérieurs.
  15. Procédé selon la revendication 14, dans lequel ladite phase non constante du rendement est une phase de rendement décroissant, le procédé comprenant :
    - l'estimation d'une valeur approximative pour la phase constante de rendement ; et
    - au moins lors de la recherche de l'indice dans ladite région de changement, l'ignorance d'au moins certaines des mesures dans ladite deuxième région moins perturbée pour lesquelles le rendement estimé est inférieur à une valeur seuil, de préférence inférieur à une fraction de la phase constante.
  16. Procédé selon la revendication 14 ou 15, dans lequel ladite phase non constante du rendement est une phase de rendement décroissant, le procédé comprenant l'identification de ladite région de changement en travaillant dans la direction des nombres indices d'amplification décroissants en partant de ladite deuxième région moins perturbée, et la détection d'un indice d'amplification approximatif pour lequel le rendement dépasse perceptiblement une valeur prédéterminée.
  17. Procédé selon la revendication 16, dans lequel la valeur estimée dudit indice d'amplification dans la région de changement est affinée, pour obtenir peut-être une valeur infime, en travaillant dans la direction des nombres indices d'amplification croissants en partant de l'indice approximatif, par détection d'un indice d'amplification pour lequel le rendement est approximativement égal à ladite valeur prédéterminée.
  18. Procédé selon l'une quelconque des revendications 1 à 17, comprenant la modélisation de ladite phase non constante du rendement par une exponentielle décroissante incluant un paramètre de réduction, et la détermination dudit paramètre de réduction à l'étape c) avec l'indice dans la région de changement par comparaison avec les mesures expérimentales.
  19. Procédé selon l'une quelconque des revendications 1 à 18, dans lequel la réaction d'amplification est une amplification en chaîne par polymérase effectuée en temps réel.
  20. Procédé selon l'une quelconque des revendications 1 à 19, dans lequel lesdites mesures sont des quantités mesurées de fluorescence émise.
  21. Installation permettant de mettre en oeuvre le procédé selon l'une quelconque des revendications 1 à 20, l'installation comprenant :
    - un support d'échantillon pour soutenir au moins l'échantillon d'intérêt ;
    - un premier appareil permettant d'appliquer ladite succession de réactions d'amplification, au moins à la population d'intérêt dans l'échantillon d'intérêt ;
    - un deuxième appareil permettant de prendre des mesures représentatives de la taille en cours de la population d'intérêt ; et
    - des moyens informatiques appropriés pour recevoir des signaux de mesure à partir du deuxième appareil et mettre en oeuvre le procédé selon la revendication 1.
  22. Produit-programme informatique permettant de conserver dans une mémoire d'une unité d'un processeur ou sur un support de mémoire amovible approprié pour coopérer avec un lecteur de ladite unité du processeur, le produit-programme comprenant des instructions pour mettre en oeuvre le procédé selon l'une quelconque des revendications 1 à 20.
EP05815440A 2004-11-24 2005-11-18 Procede, installation et programme informatique permettant d'estimer la taille initiale d'une population d'acides nucleiques, en particulier par pcr Not-in-force EP1700245B1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
FR0412471A FR2878350B1 (fr) 2004-11-24 2004-11-24 Procede installation et programme d'ordinateur pour estimer l'effectif initial d'une population d'acides nucleiques, notamment par pcr
US10/998,175 US7885767B2 (en) 2004-11-24 2004-11-29 Method, an installation, and a computer program for estimating the initial size of a population of nucleic acids, in particular by PCR
PCT/EP2005/013021 WO2006048337A1 (fr) 2004-11-24 2005-11-18 Procede, installation et programme informatique permettant d'estimer la taille initiale d'une population d'acides nucleiques, en particulier par pcr

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EP1700245A1 EP1700245A1 (fr) 2006-09-13
EP1700245B1 true EP1700245B1 (fr) 2007-06-20

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US (1) US20070260440A1 (fr)
EP (1) EP1700245B1 (fr)
AT (1) ATE365350T1 (fr)
AU (1) AU2005300646B2 (fr)
CA (1) CA2589129C (fr)
DE (1) DE602005001443T2 (fr)
ES (1) ES2289718T3 (fr)
WO (1) WO2006048337A1 (fr)

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FR2922897B1 (fr) * 2007-10-25 2009-11-27 Bio Rad Pasteur Mesure d'une population d'acides nucleiques,en particulier par pcr en temps reel.
EP2238262B1 (fr) * 2007-12-28 2019-01-16 Abbott Laboratories Analyse de discrimination allélique utilisant une valeur apparentée à l'efficacité
KR101771402B1 (ko) 2009-04-16 2017-08-25 코닌클리케 필립스 엔.브이. 핵산 정량 방법
BR112012009108A2 (pt) 2009-10-21 2019-09-17 Koninl Philips Electronics Nv método para obtenção de informação de uma curva de amplificação de uma sequência de ácido núcleico alvo, mídia legível por máquina e equipamento para a análise de amostras de ácido nucleíco
US20110276317A1 (en) 2010-04-11 2011-11-10 Life Technologies Corporation SYSTEMS AND METHODS FOR MODEL-BASED qPCR
EP2780853B1 (fr) * 2011-11-14 2019-05-01 Life Technologies Corporation Procédé et système permettant de déterminer une métrique de qualité d'amplification
US11849677B2 (en) * 2020-10-08 2023-12-26 Senslytics Corporation Method and apparatus for applying intuition technology to better preserve grains against pest damages in smart silos

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EP1700245A1 (fr) 2006-09-13
AU2005300646A1 (en) 2006-05-11
DE602005001443T2 (de) 2008-03-13
DE602005001443D1 (de) 2007-08-02
CA2589129A1 (fr) 2006-05-11
WO2006048337A1 (fr) 2006-05-11
ES2289718T3 (es) 2008-02-01
US20070260440A1 (en) 2007-11-08
ATE365350T1 (de) 2007-07-15
AU2005300646B2 (en) 2007-10-25
CA2589129C (fr) 2013-03-05

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